Vercel Composition Patterns
supabase/supabase
React composition patterns that scale. An agent skill from supabase/supabase.
Run the whole lifecycle for one spec, calling the other skills in order and advancing one legal transition at a time until it reaches a target state (default complete), stopping to ask at…
$ npx skills add changkun/wallfacer --skill wf-spec-drive -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install changkun/wallfacer wf-spec-drive --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/changkun/wallfacer.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/wf-spec-drive .claude/skills/wf-spec-drive && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "wf-spec-drive" agent skill from https://github.com/changkun/wallfacer/tree/main/.claude/skills/wf-spec-drive into .claude/skills/wf-spec-drive/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "wf-spec-drive", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/changkun/wallfacer/tree/main/.claude/skills/wf-spec-driveType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add changkun/wallfacer --skill wf-spec-drive -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install changkun/wallfacer wf-spec-drive --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/changkun/wallfacer.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.claude/skills/wf-spec-drive .agents/skills/wf-spec-drive && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "wf-spec-drive" agent skill from https://github.com/changkun/wallfacer/tree/main/.claude/skills/wf-spec-drive into .agents/skills/wf-spec-drive/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "wf-spec-drive", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add changkun/wallfacer --skill wf-spec-drive -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install changkun/wallfacer wf-spec-drive --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/changkun/wallfacer.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.claude/skills/wf-spec-drive .cursor/skills/wf-spec-drive && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "wf-spec-drive" agent skill from https://github.com/changkun/wallfacer/tree/main/.claude/skills/wf-spec-drive into .cursor/skills/wf-spec-drive/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "wf-spec-drive", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/changkun/wallfacer.git --path .claude/skills/wf-spec-drive--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add changkun/wallfacer --skill wf-spec-drive -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install changkun/wallfacer wf-spec-drive --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/changkun/wallfacer.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.claude/skills/wf-spec-drive .gemini/skills/wf-spec-drive && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "wf-spec-drive" agent skill from https://github.com/changkun/wallfacer/tree/main/.claude/skills/wf-spec-drive into .gemini/skills/wf-spec-drive/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "wf-spec-drive", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install changkun/wallfacer wf-spec-driveInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add changkun/wallfacer --skill wf-spec-drive -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/changkun/wallfacer.git skills-src && mkdir -p .github/skills && cp -r skills-src/.claude/skills/wf-spec-drive .github/skills/wf-spec-drive && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "wf-spec-drive" agent skill from https://github.com/changkun/wallfacer/tree/main/.claude/skills/wf-spec-drive into .github/skills/wf-spec-drive/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "wf-spec-drive", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add changkun/wallfacer --skill wf-spec-drive -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install changkun/wallfacer wf-spec-drive --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/changkun/wallfacer.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.claude/skills/wf-spec-drive .opencode/skills/wf-spec-drive && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "wf-spec-drive" agent skill from https://github.com/changkun/wallfacer/tree/main/.claude/skills/wf-spec-drive into .opencode/skills/wf-spec-drive/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "wf-spec-drive", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
wf-spec-driveRun the whole lifecycle for one spec, calling the other skills in order and advancing one legal transition at a time until it reaches a target state (default complete), stopping to ask at…
Wf Spec Drive is an agent skill from changkun/wallfacer. Run the whole lifecycle for one spec, calling the other skills in order and advancing one legal transition at a time until it reaches a target state (default complete), stopping to ask at irreversible gates. Use when the user wants a spec taken from wherever it is to done rather than running each step by hand — and start here when unsure which single-spec skill applies.
Its SKILL.md is about 2.3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Development. The repository describes itself as: Chat, specs, tasks, and code. An autonomous engineering platform. Full autonomy when you trust it. Full control when you don't. The licence is MIT.
4 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 9fc9f06. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Wf Spec Drive loads about 2.3k tokens when it runs. Until then it costs about 97 tokens; SKILL.md has 1,165 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from changkun/wallfacer at commit 9fc9f06, republished under its MIT licence (© changkun). 1,165 words, ~2,286 tokens.
.claude/skills/wf-spec-drive/SKILL.md (or your agent's skills folder).Advance the spec at the first argument toward a target state (default complete),
one or more legal transitions at a time, reporting the new state at the end of
every turn. This is the orchestrator: it reads reality, picks the next step, runs
the right /wf-spec-* sub-skill (or transition API call), and stops at gates.
It is built to be re-invoked: under a /goal the Stop-hook evaluator re-runs
you each turn with the remaining work, so each turn must (a) make concrete progress
and (b) end by stating the spec's current status in your message, so the
evaluator can judge whether the goal is met. Within a turn, carry the spec through
every legal, non-gated transition you can; end the turn at a gate, at the target,
or when the next step waits on work outside this session.
Seven states. status is the single source of truth; transitions must follow
the legal edges below — there is no implemented/in_progress state, and
validated → complete is ILLEGAL. A spec reaches complete only through
testing, where a drift verdict is rendered.
vague → drafted | archived
drafted → validated | stale | archived
validated → testing | stale
testing → complete | stale | archived
complete → stale | archived
stale → drafted | validated | archived
archived → drafted (resurrection)Server-automatic vs. agent-initiated:
| Edge | Who drives it |
|---|---|
| drafted → validated | agent (validate action) or folder-dispatch auto-promote |
| validated → testing | server on task-done (drift pipeline); or wrap-up for the direct path |
| testing → complete / stale | server drift verdict; or force-complete; or wrap-up's verdict |
| any → stale (fan-out) | server on task-done / chat-edit; agent may stale manually |
| any → archived, archived → drafted | agent (archive / unarchive) |
By default there is no server: advance the status by editing the spec's frontmatter along a legal edge and committing it, exactly as the other skills do.
Where a transition API is present, prefer it because it is authoritative,
validates the edge, runs drift / stale
fan-out, and commits: POST /api/specs/transition with
{ "action": "<action>", "path": "<workspace-relative spec path>" }. Actions:
dispatch, undispatch, archive, unarchive, validate, stale,
unstale, dismiss-stale, force-complete, migrate. /wf-spec-dispatch
uses the same endpoint.
Whether you edit frontmatter or call the API, only ever move along a legal
edge above. Never write an illegal jump (e.g. validated → complete).
Note there is no API action to enter testing or to complete from validated
directly; the server enters testing on task-done, and force-complete only does
testing → complete. The direct-implement path (below) therefore walks
validated → testing → complete itself.
status, dispatched_task_id, depends_on,
affects, and whether it has a child-spec directory (non-leaf).dispatched_task_id is set, check the linked task's status (done /
in_progress / failed) on the board, where one exists.complete) and confirm the spec is
not already there or past it.Match the current status and choose the next action toward the target:
| Current | Condition | Next step |
|---|---|---|
vague | — | /wf-spec-refine (or /wf-spec-create follow-up) to make it concrete → drafted. Then re-loop. |
drafted | large / many open questions | /wf-spec-breakdown (design) → child specs; then drive the lead child. Gate? No. |
drafted | small, items clear | /wf-spec-validate (lint), then validate action → validated. |
validated | leaf, build in one pass | /wf-spec-implement (direct, autonomous mode — no plan-mode pause under a goal), which finishes via /wf-spec-wrapup (testing→complete). |
validated | wants board execution | GATE: dispatching to the board is outward — confirm with the user, then /wf-spec-dispatch. |
validated | non-leaf with task children | dispatch/implement each leaf (drive children); parent completes when leaves do. |
testing | task done, server idle | /wf-spec-wrapup renders the verdict → complete or stale. |
testing | tester failed (testing_pending) | report; offer force-complete (a gate — confirm). |
complete | — | At target. If the user wanted downstream specs driven, pick the next unblocked dependent. |
stale | — | /wf-spec-refine → drafted/validated, then re-loop. |
archived | — | Stop unless the user asked to resurrect (unarchive → drafted). |
Dependencies: before implementing/dispatching, confirm every depends_on is
complete (per the sub-skills' own gates). If a dependency is not complete and the
target requires it, drive the dependency first or report the block.
Pause and ask the user (do not execute) when the next step is:
stale on a spec with dependents.force-complete (overrides the drift gate).For all other steps (refine, validate, breakdown, implement-direct, wrap-up of a spec you implemented this run), proceed without pausing.
Run the chosen sub-skill / API call. Make all the non-gated, legal progress you can in this turn (e.g. validate → implement → wrap-up is one turn for a small leaf); stop at the first gate, the target, or a step that waits on work outside this session, such as a dispatched board task.
End every turn with a status line the goal evaluator can read, e.g.:
Spec <path>: status <old> → <new>. Target: <target>. Next: <next step | GATE: <what> | DONE>./goal (what is and isn't truly hands-off)A user sets, e.g., /goal spec <path> reaches status complete. Each turn the
Stop-hook evaluator reads your transcript; if the spec is not yet at the target it
re-invokes you with what remains. You don't manage the loop: you make and report
progress each turn. The harness pauses the goal when the evaluator keeps finding
it unmet, and clears it when met.
Be honest about the reach of an unattended loop (no human watching):
refine,
validate, breakdown, implement (autonomous mode, no plan-mode pause), and
wrap-up through the testing gate. A small validated leaf can therefore go all
the way to complete unattended.force-complete, stale fan-out). The evaluator can't approve them and
can't run commands, so an unattended loop cannot pass them, and repeated unmet
checks pause the goal. When you reach a gate, state it plainly and end the
turn: report "GATE: <what> (needs you)", so when the user returns they can
unblock with one message./wf-spec-drive (or /wf-spec-wrapup)
to pick up testing → complete.Net: /goal + /wf-spec-drive runs the in-session path to complete hands-off,
and turns every outward/async step into a clearly-reported stop rather than a
silent hang. Don't claim more autonomy than that.
validated → testing → complete/stale on task-done. Don't hand-set its
status; let the server, then run /wf-spec-wrapup only to enrich the Outcome.status line is the
contract with the goal evaluator; keep it accurate.© changkun, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in .claude/skills/wf-spec-drive of changkun/wallfacer.
Open the folder on GitHubat commit 9fc9f06
Wf Spec Drive next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Wf Spec Drive this skillchangkun/wallfacer | 112 | — | ~2.3k | Automated safety check: Pass | MIT | |
| Vercel Composition Patternssupabase/supabase | 111k | 58 repos | ~726 | Automated safety check: Pass | MIT | |
| Finishing a Development Branchobra/superpowers | 297k | 5 repos | ~1.9k | Automated safety check: Pass | MIT | |
| Typescript Advanced Typesrolling-scopes/rsschool-app | 10k | 25 repos | ~4.2k | Automated safety check: Pass | MPL-2.0 | |
| PR Babysitteropeninterpreter/openinterpreter | 69k | 3 repos | ~4.2k | Automated safety check: Pass | Apache-2.0 | |
| Code Review ChecklistshareAI-lab/learn-claude-code | 78k | 4 repos | ~1.1k | Automated safety check: Pass | MIT |
supabase/supabase
React composition patterns that scale. An agent skill from supabase/supabase.
obra/superpowers
Walks the last step of a branch: confirm tests pass, detect the git environment, ask how to integrate, carry out your choice and clean up the worktree.
rolling-scopes/rsschool-app
Master TypeScript's advanced type system including generics, conditional types, mapped types, template literals, and utility types for building type-safe applications.
openinterpreter/openinterpreter
Watches an open GitHub pull request until it merges, handling review comments, diagnosing CI failures and retrying flaky checks along the way.
shareAI-lab/learn-claude-code
Reviews code against a five-part checklist covering security, correctness, performance, maintainability and testing, and reports findings in a fixed format.
onyx-dot-app/onyx
Iteratively improves a PR (GitHub), MR (GitLab), or shelved changelist (Perforce) until Greptile gives it a 5/5 confidence score with zero unresolved comments.
changkun/wallfacer
Split one spec into children — sub-design specs when questions are still open, or implementation-ready leaves when the plan is clear.
changkun/wallfacer
Write a new spec from scratch when none exists for the idea yet.
changkun/wallfacer
Mark a validated spec ready to build and resolve its dependency wiring; where a task board with a transition API is present, create the linked task atomically.
changkun/wallfacer
Survey the whole spec tree: what is complete, in progress, blocked, and actionable next.
changkun/wallfacer
Read-only verdict on whether an implementation meets its spec: each acceptance criterion classified, unintended changes flagged, test coverage checked.
changkun/wallfacer
Structural lint over the spec tree — required frontmatter fields, valid status and effort values, track location, DAG acyclicity, dispatch consistency, orphans, status consistency.
Categories
Run the whole lifecycle for one spec, calling the other skills in order and advancing one legal transition at a time until it reaches a target state (default complete), stopping to ask at…. Wf Spec Drive is an agent skill from changkun/wallfacer. Run the whole lifecycle for one spec, calling the other skills in order and advancing one legal transition at a time until it reaches a target state (default complete), stopping to ask at irreversible gates.
Wf Spec Drive fits situations like: development work in your project.
Run `npx skills add changkun/wallfacer --skill wf-spec-drive -a claude-code`. Or copy the skill folder (.claude/skills/wf-spec-drive in changkun/wallfacer) into .claude/skills/wf-spec-drive in your project. Claude Code loads it when a task matches its description.
Run `npx skills add changkun/wallfacer --skill wf-spec-drive -a codex`. Or copy the skill folder (.claude/skills/wf-spec-drive in changkun/wallfacer) into .agents/skills/wf-spec-drive in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add changkun/wallfacer --skill wf-spec-drive -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/wf-spec-drive, .gemini/skills/wf-spec-drive, .github/skills/wf-spec-drive and .opencode/skills/wf-spec-drive in your project.
SKILL.md names no scripts, command-line tools or credentials: Wf Spec Drive is instructions for the agent only.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Wf Spec Drive is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.3k tokens (SKILL.md is roughly 9.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Wf Spec Drive: Vercel Composition Patterns (supabase/supabase, 111k stars), Finishing a Development Branch (obra/superpowers, 297k stars), Typescript Advanced Types (rolling-scopes/rsschool-app, 10k stars) and PR Babysitter (openinterpreter/openinterpreter, 69k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
changkun (a GitHub user) maintains it in changkun/wallfacer, which has 112 GitHub stars. The repository holds 14 skills in this directory. The repository was last updated on October 9, 2026.
Source: changkun/wallfacer on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.